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--- |
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license: other |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Xanadu00/galaxy_classifier_mobilevit_2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# Xanadu00/galaxy_classifier_mobilevit_2 |
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This model is a fine-tuned version of [apple/mobilevit-small](https://huggingface.co/apple/mobilevit-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.1727 |
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- Train Accuracy: 0.9423 |
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- Validation Loss: 0.4766 |
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- Validation Accuracy: 0.8565 |
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- Epoch: 17 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- optimizer: {'name': 'AdamW', 'weight_decay': 0.004, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'ExponentialDecay', 'config': {'initial_learning_rate': 0.002, 'decay_steps': 10000, 'decay_rate': 0.01, 'staircase': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |
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|:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
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| 0.9904 | 0.6535 | 0.7897 | 0.7269 | 0 | |
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| 0.6759 | 0.7662 | 0.5772 | 0.8030 | 1 | |
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| 0.5845 | 0.7979 | 0.5967 | 0.8010 | 2 | |
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| 0.5166 | 0.8232 | 0.5613 | 0.8030 | 3 | |
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| 0.4819 | 0.8330 | 0.5049 | 0.8253 | 4 | |
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| 0.4432 | 0.8516 | 0.5894 | 0.7993 | 5 | |
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| 0.4113 | 0.8580 | 0.4722 | 0.8354 | 6 | |
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| 0.3802 | 0.8704 | 0.4730 | 0.8444 | 7 | |
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| 0.3529 | 0.8750 | 0.4391 | 0.8543 | 8 | |
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| 0.3255 | 0.8836 | 0.4380 | 0.8563 | 9 | |
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| 0.3053 | 0.8953 | 0.4468 | 0.8532 | 10 | |
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| 0.2821 | 0.9027 | 0.5082 | 0.8368 | 11 | |
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| 0.2690 | 0.9071 | 0.4380 | 0.8588 | 12 | |
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| 0.2460 | 0.9132 | 0.4668 | 0.8540 | 13 | |
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| 0.2184 | 0.9247 | 0.4684 | 0.8557 | 14 | |
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| 0.2017 | 0.9273 | 0.4880 | 0.8546 | 15 | |
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| 0.1930 | 0.9311 | 0.4934 | 0.8582 | 16 | |
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| 0.1727 | 0.9423 | 0.4766 | 0.8565 | 17 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- TensorFlow 2.12.0 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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